There are 1 repository under icml-2020 topic.
Implementations of few-shot object detection benchmarks
code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"
Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.
A list of the top 10 computer vision papers in 2020 with video demos, articles, code and paper reference.
Official Pytorch implementation of ReBias (Learning De-biased Representations with Biased Representations), ICML 2020
[ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels
Repository of the ICML 2020 paper "Set Functions for Time Series"
Official implementation of the paper Stochastic Latent Residual Video Prediction
Code for reproducing results in ICML 2020 paper "PackIt: A Virtual Environment for Geometric Planning"
Benchmarking continual learning techniques for Human Activity Recognition data. We offer interesting insights on how the performance techniques vary with a domain other than images.
Code for "Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources". (ICML 2020)
Code repo for Gradient Temporal-Difference Learning with Regularized Corrections paper.
Official PyTorch implementation of Time-aware Large Kernel (TaLK) Convolutions (ICML 2020)
Reproducing RigL (ICML 2020) as a part of ML Reproducibility Challenge 2020
Code for Non-convex Learning via Replica Exchange Stochastic Gradient MCMC, ICML 2020.
[ICML 2020] Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies. https://arxiv.org/abs/2007.12678, https://icml.cc/virtual/2020/poster/5797
Code-repository for the ICML 2020 paper Fairwashing explanations with off-manifold detergent
The implementation for the paper "On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm".
Code for "Adversarial Robustness via Runtime Masking and Cleansing" (ICML 2020)
This project contains the code for the paper accepted at NeurIPS 2020 - Robust Meta-learning for Mixed Linear Regression with Small Batches.
Implementation of the paper "Learning Cancer Progression Network from Mutation Allele Frequencies", ICML Compbio 2020
Code for generating data in ICML 2020 paper "PackIt: A Virtual Environment for Geometric Planning"
Code associated with "Recourse For Humans", presented at the Participatory Approaches to Machine Learning workshop at ICML 2020.
Code for the paper "The Probabilistic Fault Tolerance of Neural Networks in the Continuous Limit", ICML 2020
A Systematic Comparison of Robustness in Bayesian Deep Learning on Diabetic Retinopathy Diagnosis Tasks